Performs a series of offline and/or online change-point detection algorithms for 1) univariate mean; 2) univariate polynomials; 3) univariate and multivariate nonparametric settings; 4) high-dimensional covariances; 5) high-dimensional networks with and without missing values; 6) high-dimensional linear regression models; 7) high-dimensional vector autoregressive models; 8) high-dimensional self exciting point processes; 9) dependent dynamic nonparametric random dot product graphs; 10) univariate mean against adversarial attacks. For more informations, see <arXiv:1810.09498>; <arXiv:2006.03283>; <arXiv:2007.09910>; <arXiv:1905.10019>; <arXiv:1910.13289>; <arXiv:1712.09912>; <arXiv:1809.09602>; <arXiv:1911.07494>; <arXiv:2101.05477>; <arXiv:2010.10410>; <arXiv:1909.06359>; <arXiv:2006.03572>; <arXiv:2110.06450>; <arXiv:2105.10417>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, gglasso, glmnet, ks, MASS, data.tree, Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, abind, DiagrammeR, rmarkdown |
| Published: | 2021-12-10 |
| Author: | Haotian Xu [aut, cre], Oscar Padilla [aut], Daren Wang [aut], Mengchu Li [aut], Qin Wen [ctb] |
| Maintainer: | Haotian Xu <haotian.xu at warwick.ac.uk> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/HaotianXu/changepoints |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | changepoints results |
| Reference manual: | changepoints.pdf |
| Vignettes: |
example_VAR example_univariate_mean |
| Package source: | changepoints_1.0.0.tar.gz |
| Windows binaries: | r-devel: changepoints_1.0.0.zip, r-release: changepoints_1.0.0.zip, r-oldrel: changepoints_1.0.0.zip |
| macOS binaries: | r-release (arm64): changepoints_1.0.0.tgz, r-oldrel (arm64): changepoints_1.0.0.tgz, r-release (x86_64): changepoints_1.0.0.tgz, r-oldrel (x86_64): changepoints_1.0.0.tgz |
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